The fear of missing a wave of market opportunity fueled by the rapid adoption of ChatGPT is driving investment in AI training infrastructure, from servers configured with highly performant, power-hungry co-processors to high-speed networks and storage. Building and powering a data center optimized for AI training means higher rack densities, enabled by new cooling strategies and design principles. Commercializing large-scale generative AI applications then requires a highly optimized and distributed army of servers with co-processors optimized for low-cost computing.
The breadth of solutions available as a service continues to push the boundaries of the imagination. From abstract offerings like savings as a service, to extremely high-value products such as high-performance computing clusters, microgrids, and entire data, the increasing cost of capital has turned XaaS into a top enterprise growth strategy. Some telecom giants have made significant strides to move their entire virtual network to the cloud, opting to run it as a service, and we now expect many more to follow suit. The growth of XaaS will continue to fuel the FinOps movement as managing costs and maximizing the value of invested capital remains at the top of the enterprise agenda.
Bill MorelliChief Research Officer and Research Vice President, Enterprise ITbill.morelli@omdia.com
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